Dietary concentrate supplementation increases milk production and reduces predicted greenhouse gas emission intensity in pasture-based commercial dairy farms

Controlled studies have extensively documented that concentrate supplements typically increase enteric CH4 emissions and milk yield and reduce emissions per unit of milk produced and dry matter intake. However, no studies have been conducted to determine the effect of concentrate on predicted greenhouse gas emissions from dairy farms representing the Australian pasture-based farming system. Thus, this study sought to determine how dietary concentrate supplementation affects enteric and manure CH4, and N2O of Australian pasture-based dairy farms. The Australian Dairy Carbon Calculator was used, which incorporates emission factors and methodologies used in the National Greenhouse Gas Inventory as reported to the Intergovernmental Panel on Climate Change. Primary data were collected and analyzed from 120 commercial farms in Australia's major dairy regions. Then the farms were divided into 4 groups based on their dietary concentrate supplementation: ≤1 (low; 15 farms), 1 to 2 (moderate; 35 farms), 2 to 3 (high; 35 farms), and ≥3 (very high; 35 farms) t of concentrate dry matter (tDM) per cow per year. Sources of greenhouse gas emissions were CO2 from concentrate production, enteric CH4, and manure CH4 and N2O. Total dry matter intake, milk yield, and daily enteric CH4 production (g/d) quadratically increased with concentrate level, whereas greenhouse gas emission intensity of milk production (kg of CO2 equivalent per kg of fat- and protein-corrected milk) decreased by 14% for farms supplementing with ≥3 tDM/cow per year compared with those supplementing with ≤1 tDM/cow per year of dietary concentrate. The N2O and CH4 emissions from manure increased quadratically and linearly, respectively, with the increasing supplementation of concentrate. Farms supplementing 2 to 3 tDM/cow per year showed substantial increases in gross income, gross margin, earnings before interest and tax, and net income ($/cow per year) compared with those supplementing of ≤1, 1 to 2, and ≥3 tDM/cow per year. Overall, increasing dietary concentrate supplementation for dairy cows resulted in increased milk production per cow, reduced greenhouse gas emissions per unit of milk produced, and increased income and profit. However, a comprehensive life cycle assessment study is needed to account for carbon sequestration by other farm components, such as pastures and trees, which were not considered in the present study. In addition, the present study was based on modeling and did not gather ground truth information for DMI, digestibility, crude protein, and urinary and fecal N excretion. Therefore, data should be interpreted with caution, and studies gathering such information are encouraged.

Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing

Precision in grazing management is highly dependent on accurate pasture monitoring. Typically, this is often overlooked because existing approaches are labour-intensive, need calibration, and are commonly perceived as inaccurate. Machine-learning processes harnessing big data, including remote sensing, can offer a new era of decision-support tools (DST) for pasture monitoring. Its application on-farm remains poor because of a lack of evidence about its accuracy. This study aimed at evaluating and quantifying the minimum data required to train a machine-learning satellite-based DST focusing on accurate pasture biomass prediction using this approach. Management data from 14 farms in New South Wales, Australia and measured pasture biomass throughout 12 consecutive months using a calibrated rising plate meter (RPM) as well as pasture biomass estimated using a DST based on high temporal/spatial resolution satellite images were available. Data were balanced according to farm and week of each month and randomly allocated for model evaluation (20%) and for progressive training (80%) as follows: 25% training subset (1W: week 1 in each month); 50% (2W: week 1 and 3); 75% (3W: week 1, 3, and 4); and 100% (4W: week 1 to 4). Pasture biomass estimates using the DST across all training datasets were evaluated against a calibrated rising plate meter (RPM) using mean-absolute error (MAE, kg DM/ha) among other statistics. Tukey's HSD test was used to determine the differences between MAE across all training datasets. Relative to the control (no training, MAE: 498 kg DM ha-1) 1W did not improve the prediction accuracy of the DST (P > 0.05). With the 2W training dataset, the MAE decreased to 342 kg DM ha-1 (P < 0.001), while for the other training datasets, MAE decreased marginally (P > 0.05). This study accounts for minimal training data for a machine-learning DST to monitor pastures from satellites with comparable accuracy to a calibrated RPM which is considered the 'gold standard' for pasture biomass monitoring.

Graduate Student Literature Review: System, plant, and animal factors controlling dietary pasture inclusion and their impact on ration formulation for dairy cows

Diet formulation in a pasture-based dairy system is a challenge as the quality and quantity of available pasture, which generally constitutes the base diet, is constantly changing. The objective of this paper is to cover a more in-depth review of the nutritional characteristics of pasture-based diets, identifying potential system, plant, and animal factors that condition pasture dietary inclusion in dairy cows. In practice, there is a wide diversity of pasture-based systems with predominant to minimal use of pasture requiring a more specific classification that potentially considers the amount and time of access to pasture, access to housing, length of grazing season, seasonality of calving, and level and method of supplementation. There are important differences in the nutritional quality between pasture species and even cultivars. However, under management practices that promote maintenance of pasture in a vegetative state as well as controlling the availability of pasture, it is possible to achieve high dry matter intakes (∼2.9%-3.4% of live weight) of pasture with moderate to high diet energy density, protein supply, and digestibility. The amount of pasture to include in the diet will depend on several factors, such as the type of production system, the cost of supplementary feeds, and the farmer's objectives, but inclusions of ∼40% to 50% of the diet seem to potentially reduce costs while apparently not limiting voluntary feed intake. Considering that there seems to be a continuum of intermediate management systems, a better understanding of the factors inherent to the feed ingredients used, as well as the use of nutrients by cows, and potential interactions between animal × system should be addressed in greater depth. This requires a meta-analysis approach, but given the diversity of the pasture-based system in practice, the existing information is highly fragmented. A clear definition of "subsystems" is necessary to direct the future research and development of mechanistic models.

Verifying origin claims on dairy products using stable isotope ratio analysis and random forest classification

Scientifically underpinning geographic origin claims will improve consumer trust in food labels. Stable isotope ratio analysis (SIRA) is an analytical technique that supports origin verification of food products based on naturally occurring differences in isotopic compositions. SIRA of five relevant elements (C, H, N, O, S) was conducted on casein isolated from butter (n = 60), cheese (n = 96), and whole milk powder (WMP) (n = 41). Samples were divided into four geographic regions based on their commercial origin: Ireland (n = 79), Europe (n = 67), Australasia (n = 29) and USA (n = 22). A random forest machine learning model built using δ13C, δ2H, δ15N, δ18O and δ34S values of all products (n = 197) accurately (88% model accuracy rate) predicted the region of origin with class accuracy of 95% for Irish, 84% for European, 71% for Australasia, and 94% for US products.

Including 8 hours of access to alfalfa in 1 or 2 grazing sessions in dairy cows fed a partial mixed ration: Effects on intake, behavior, digestion, and milk production and composition

The aim of this study was to evaluate the inclusion of alfalfa grazing during 8 h continuous or partitioned in 2 separated sessions of 4 h after each milking, on nutrient intake, digestibility, ruminal fermentation, feeding behavior, milk production, milk composition, and milk fatty acid profile, in late-lactation cows fed a partial mixed ration (PMR). Twelve dairy cows (193 ± 83 d in milk, 584 ± 71 kg of body weight) were housed in individual outdoor pens and assigned to treatments according to a 3 × 3 Latin square design replicated 4 times. The treatments were as follows: (1) control (T0), cows were fed a total mixed ration (TMR) provided ad libitum 20.0% crude protein (CP), 32.2% neutral detergent fiber (NDF); (2) fed a diet combining a PMR which had the same ingredient composition as the TMR (60% of ad libitum intake) + 1 session of 8 h of pasture (T8), continuous grazing alfalfa (Medicago sativa; 20.6% CP, 35.8% NDF) after the p.m. milking; and (3) PMR (60% of ad libitum intake) + 2 daily sessions of 4 h of access to pasture after each milking (T4+4). The experiment lasted 57 d and was divided into 3 periods of 19 d each. The first 12 d of each period was used for diet adaptation, and the last 7 d was used for data collection. No differences among treatments were observed for any of the productive variables, feeding efficiency, or purine derivatives excretion. Cows in T0 had greater intake and apparent digestibility of dry matter, organic matter, and nonfibrous carbohydrates compared with T4+4 and T8. Compared with T0, alfalfa grazing increased the concentration of C18:1 trans-11 and decreased those of C16:0 and C17:0 in milk fat. Cows in T4+4 consumed 1.1 more kg DM/d of alfalfa and N provided by alfalfa in the diet was 3 percentage points higher compared with T8 cows (266 vs. 229 g/d, respectively). In addition, T4+4 cows had a greater daily range of ruminal pH than T8 (0.73 vs. 0.93), and the highest concentrations of NH3-N were recorded during the a.m. grazing session while in T8 cows it occurred during the night. In conclusion, including 8 h of alfalfa grazing in T8 and T4+4 treatments allowed the substitution between 35.8 and 38.7% of the total dry matter intake (DMI) of a PMR (with a similar CP concentration to alfalfa) for pasture, maintaining milk solids production and increasing the C18:1 trans-11 of milk fat compared with a TMR in mid late-lactation cows. In an herbage plus PMR diet, splitting the 1 continuous grazing session of 8 h into 2 sessions of 4 h increased the proportion of energy and N provided by alfalfa pasture and reduced PMR intake, without modifying the total nutrient intake or productive performance of cows.

Bacterial culture and antimicrobial susceptibility results from bovine milk samples submitted to four veterinary diagnostic laboratories in Australia from 2015 to 2019

A 5-year retrospective study was conducted to describe the mastitis-causing organisms isolated from bovine milk samples submitted to four veterinary diagnostic laboratories in Australia. The aim of this study was to identify temporal, geographical, and seasonal patterns of occurrence for the organisms and report the in vitro susceptibility of the most common mastitis-causing pathogens. In total, 22,102 milk samples were submitted between 2015 and 2019. The results were reported as positive growth for at least one significant organism (n = 11,407; 51.6%), no growth (n = 5,782; 26.2%), and mixed/contaminated growth (n = 4,913; 22.2%). Culture results for no growth, gram-negative bacteria, and eukaryotic organisms were combined for each region, and they were accounted for between 23 and 46% of submissions. These results represent a subset of mastitis cases for which the antibiotic treatment may not be warranted. A total of 11,907 isolates were cultured from 11,407 milk samples. The most common isolated organisms were Streptococcus uberis [41.3%; 95% confidence interval (CI): 40.4-42.1%] and Staphylococcus aureus (23.6%; 95% CI: 22.8-24.3%). For S. uberis and S. aureus, there was an association between a positive culture result and the dairy region. All regions except for the Sub-tropical Dairy region were more likely to culture S. uberis compared to the reference, Dairy NSW (P < 0.001). Similarly, for S. aureus, a positive culture result was more likely in all other dairy regions compared to Dairy NSW (P < 0.001). The LISA cluster analysis identified differences between High-High (hotspot) postcodes for S. aureus and S. uberis throughout all the analyzed dairy regions. These results highlight the need for further investigations into specific risk factors, such as environmental factors and herd-level predictors, which may have influenced the observed regional variations. Common mastitis-causing pathogens showed overall good susceptibility to a range of antimicrobials used in the treatment of mastitis. On-going surveillance of mastitis-causing pathogens and their antimicrobial susceptibilities will facilitate targeted mastitis control and treatment programs.

Field and in-silico analysis of harvest index variability in maize silage

Maize silage is a key component of feed rations in dairy systems due to its high forage and grain yield, water use efficiency, and energy content. However, maize silage nutritive value can be compromised by in-season changes during crop development due to changes in plant partitioning between grain and other biomass fractions. The partitioning to grain (harvest index, HI) is affected by the interactions between genotype (G) × environment (E) × management (M). Thus, modelling tools could assist in accurately predicting changes during the in-season crop partitioning and composition and, from these, the HI of maize silage. Our objectives were to (i) identify the main drivers of grain yield and HI variability, (ii) calibrate the Agricultural Production Systems Simulator (APSIM) to estimate crop growth, development, and plant partitioning using detailed experimental field data, and (iii) explore the main sources of HI variance in a wide range of G × E × M combinations. Nitrogen (N) rates, sowing date, harvest date, plant density, irrigation rates, and genotype data were used from four field experiments to assess the main drivers of HI variability and to calibrate the maize crop module in APSIM. Then, the model was run for a complete range of G × E × M combinations across 50 years. Experimental data demonstrated that the main drivers of observed HI variability were genotype and water status. The model accurately simulated phenology [leaf number and canopy green cover; Concordance Correlation Coefficient (CCC)=0.79-0.97, and Root Mean Square Percentage Error (RMSPE)=13%] and crop growth (total aboveground biomass, grain + cob, leaf, and stover weight; CCC=0.86-0.94 and RMSPE=23-39%). In addition, for HI, CCC was high (0.78) with an RMSPE of 12%. The long-term scenario analysis exercise showed that genotype and N rate contributed to 44% and 36% of the HI variance. Our study demonstrated that APSIM is a suitable tool to estimate maize HI as one potential proxy of silage quality. The calibrated APSIM model can now be used to compare the inter-annual variability of HI for maize forage crops based on G × E × M interactions. Therefore, the model provides new knowledge to (potentially) improve maize silage nutritive value and aid genotype selection and harvest timing decision-making.

A Forage Allowance by Forage Type Interaction Impacts the Daily Milk Yield of Early Lactation Dairy Cows

We tested for a forage allowance effect on the milk yield of early lactation dairy cow herds grazing swards sown with perennial ryegrass (Lolium perenne L.), white clover (Trifolium repens L.) and plantain (Plantago lanceolata L.) relative to perennial ryegrass alone. The examined allowances consisted of offering 12, 14, 16, 18, 20 or 25 kg of dry matter (DM)/cow per day of grazeable herbage, with diverse swards sown as mixtures and spatially adjacent monocultures. After adapting cows to their assigned forage type for 8 days, treatment effects on milk yield and composition, blood metabolites (beta-hydroxybutyrate, non-esterified fatty acids and urea concentrations), body weight change, forage intake and selection differentials for forage species and certain nutrients were monitored over 7 days. We confirmed a forage allowance effect on milk yield improvements in dairy cows grazing diverse swards relative to perennial ryegrass monocultures. Improvements in milk yield were evident at forage allowances of 14 to 20 kg of DM/cow per day, diminishing at the highest allowance of 25 kg of DM/cow per day. Improvements in milk yield for the mixture and spatially adjacent monocultures peaked at forage allowances of 18 and 16 kg of DM/cow per day, equalling increases of 1.3 and 1.2 kg of milk/cow per day, respectively.

Dairy Trade Helps to Alleviate Global Carbon Emission Pressure

Global dairy production, consumption, and trade are growing rapidly, driven by population and per capita income growth and increasing health concerns mainly from developing countries, which has aroused concerns about the related carbon emission (mostly in the form of methane) increase. If all of the dairy products consumed were produced locally/domestically in the developing countries/economies (a counterfactual scenario), the carbon emissions in 2018 would be 28 Mt CO₂-equiv higher than its status quo (a factual scenario). The present study indicates that unlike in many global trade cases in which carbon leakages are from developed to developing countries, global dairy trade is characterized by net embodied carbon flows from developed to developing countries/economies due to the fact that there is an overwhelming one-way-flow of dairy products from developed to developing countries/economies. The differences in the carbon emission factors between the developed and developing countries/economies provide an opportunity that global dairy trade and production specialization can help to reduce carbon emissions from increasing dairy product demand, and the total reduction potential is estimated to be about 414 Mt CO₂-equiv from 2018 to 2030. Free trade agreements such as the Regional Comprehensive Economic Partnership will incentivize larger carbon emission reduction benefits through promoting dairy trade.

Nitrogen Use Efficiency and Excretion in Grazing Cows with High and Low Milk Urea Nitrogen Breeding Values

Milk urea nitrogen content is moderately heritable and is phenotypically related to urine nitrogen (UN). Based on this relationship, it has been suggested that genetic selection for lower milk urea nitrogen in grazing dairy cows could decrease UN concentration thereby reducing nitrogen excretions into the ground. The objective of this study was to compare the nitrogen use efficiency (NUE) and excretion in grazing cows with high and low milk urea nitrogen breeding values (MUNBV) in two farms of contrasting farming intensity. On the high-intensity farm (HIF) 68 and 70 cows with low and high MUNBV, respectively, were fed higher levels of supplementation and milked twice-daily, while on the low-intensity farm (LIF) 82 and 86 cows with low and high MUNBV, respectively, were fed lower levels of supplementation milked once-daily. Nitrogen use efficiency (g/g) was calculated as the ratio of daily milk N to daily N intake. Daily N intake (g/day) was derived from feed intake estimates based on energy requirements. The UN (g/day) was estimated by back-calculation from dietary N and subtracting milk N, faecal N, and N retained in body tissues. Irrespective of farm, cows with low MUNBV had significantly lower MY and milk urea nitrogen (p < 0.001) but this was not linked to significantly less UN. In the LIF, cows with low MUNBV had lower NUE (p < 0.001) than cows with high MUNBV, and this was explained by the reduced protein yield (p < 0.001). Selecting cows for low MUNBV was not an effective tool to reduce N losses and to increase the NUE in two dairy farms of contrasting farming intensity.

Invited review: A 2020 perspective on pasture-based dairy systems and products

Grazing pasture is the basis for dairy production systems in regions with temperate climates, such as in Ireland, New Zealand, parts of Australia, the United States, and Europe. Milk and dairy products from cows on pasture-based farms predominantly consuming fresh grazed grass (typically classified as "grass-fed" milk) have been previously shown to possess a different nutrient profile, with potential nutritional benefits, compared with conventional milk derived from total mixed ration. Moreover, pasture-based production systems are considered more environmentally and animal welfare friendly by consumers. As such, there is significant potential for market capitalization on grass-fed dairy products. As competition in this space increases, the regulations of what constitutes as grass-fed vary between different regions of the world. With this in mind, there is a need for clear and independently accredited grass-fed standards, defining the grass-fed criteria for labeling of products as such, subsequently increasing the clarity and confidence for the consumer. This review outlines the numerous effects of pasture production systems on dairy product composition, nutritional profile, and sustainability, and highlights potential future methods for authentication.

Can Nitrogen Excretion of Dairy Cows Be Reduced by Genetic Selection for Low Milk Urea Nitrogen Concentration?

The objectives of this study were two-fold. Firstly, to estimate the likely correlated responses in milk urea nitrogen (MUN) concentration, lactation yields of milk (MY), fat (FY) and crude protein (CPY) and mature cow liveweight (LWT) under three selection scenarios which varied in relative emphasis for MUN; 0% relative emphasis (MUN_0%: equivalent to current New Zealand breeding worth index), and sign of the economic value; 20% relative emphasis positive selection (MUN_+20%), and 20% relative emphasis negative selection (MUN_-20%). Secondly, to estimate for these three scenarios the likely change in urinary nitrogen (UN) excretion under pasture based grazing conditions. The predicted genetic responses per cow per year for the current index were 16.4 kg MY, 2.0 kg FY, 1.4 kg CPY, -0.4 kg LWT and -0.05 mg/dL MUN. Positive selection on MUN in the index resulted in annual responses of 23.7 kg MY, 2.0 kg FY, 1.4 kg CPY, 0.6 kg LWT and 0.10 mg/dL MUN, while negative selection on MUN in the index resulted in annual responses of 5.4 kg MY, 1.6 kg FY, 1.0 kg CPY, -1.1 kg LWT and -0.17 mg/dL MUN. The MUN_-20% reduced both MUN and cow productivity, whereas the MUN_+20% increased MUN, milk production and LWT per cow. Per cow dry matter intake (DMI) was increased in all three scenarios as milk production increased compared to base year, therefore stocking rate (SR) was adjusted to control pasture cover. Paradoxically, ten years of selection with SR adjusted to maintain annual feed demand under the MUN_+20% actually reduced per ha UN excretion by 3.54 kg, along with increases of 63 kg MY, 26 kg FY and 16 kg CPY compared to the base year. Ten years of selection on the MUN_0% index generated a greater reductions of 10.45 kg UN and 30 kg MY, and increases of 32 kg FY and 21 kg CPY per ha, whereas the MUN_-20% index reduced 14.06 kg UN and 136 kg MY with increases of 32 kg FY and 18 kg CPY compared to base year. All three scenarios increased partitioning of nitrogen excreted as feces. The selection index that excluded MUN was economically beneficial in the current economic circumstances over selection indices including MUN regardless of whether selection was either for or against MUN. There was no substantial benefit from an environmental point of view from including MUN in the Breeding Worth index, because N leaching is more a function of SR rather than of individual cow UN excretion. This study demonstrates that attention needs to be paid to the whole system consequences of selection for environmental outcomes in pastoral grazing circumstances.

Investigation of On-Farm Transmission Routes for Contamination of Dairy Cows with Top 7 Escherichia coli O-Serogroups

Shiga toxin-producing Escherichia coli (STEC) are foodborne bacterial pathogens, with cattle a significant reservoir for human infection. This study evaluated environmental reservoirs, intermediate hosts and key pathways that could drive the presence of Top 7 STEC (O157:H7, O26, O45, O103, O111, O121 and O145) on pasture-based dairy herds, using molecular and culture-based methods. A total of 235 composite environmental samples (including soil, bedding, pasture, stock drinking water, bird droppings and flies and faecal samples of dairy animals) were collected from two dairy farms, with four sampling events on each farm. Molecular detection revealed O26, O45, O103 and O121 as the most common O-serogroups, with the greatest occurrence in dairy animal faeces (> 91%), environments freshly contaminated with faeces (> 73%) and birds and flies (> 71%). STEC (79 isolates) were a minor population within the target O-serogroups in all sample types but were widespread in the farm environment in the summer samplings. Phylogenetic analysis of whole genome sequence data targeting single nucleotide polymorphisms revealed the presence of several clonal strains on a farm; a single STEC clonal strain could be found in several sample types concurrently, indicating the existence of more than one possible route for transmission to dairy animals and a high rate of transmission of STEC between dairy animals and wildlife. Overall, the findings improved the understanding of the ecology of the Top 7 STEC in open farm environments, which is required to develop on-farm intervention strategies controlling these zoonoses.

The Fusion of Spectral and Structural Datasets Derived from an Airborne Multispectral Sensor for Estimation of Pasture Dry Matter Yield at Paddock Scale with Time

This study aimed to develop empirical pasture dry matter (DM) yield prediction models using an unmanned aerial vehicle (UAV)-borne sensor at four flying altitudes. Three empirical models were developed using features generated from the multispectral sensor: Structure from Motion only (SfM), vegetation indices only (VI), and in combination (SfM+VI) within a machine learning modelling framework. Four flying altitudes were tested (25 m, 50 m, 75 m and 100 m) and based on independent model validation, combining features from SfM+VI outperformed the other models at all heights. However, the importance of SfM-based features changed with altitude, with limited importance at 25 m but at all higher altitudes SfM-based features were included in the top 10 features in a variable importance plot. Based on the independent validation results, data generated at 25 m flying altitude reported the best model performances with model accuracy of 328 kg DM/ha. In contrast, at 100 m flying altitude, the model reported an accuracy of 402 kg DM/ha which demonstrates the potential of scaling up this technology at farm scale. The spatial-temporal maps provide valuable information on pasture DM yield and DM accumulation of herbage mass over the time, supporting on-farm management decisions.

Systematic Review and Meta-Analysis: Identification of Factors Influencing Milking Frequency of Cows in Automatic Milking Systems Combined with Grazing

More dairy farms (up to more than one in four in some countries) are equipped with automatic milking systems (AMS) worldwide. Because of the positive impacts of grazing, e.g., on animal welfare or on production costs, numerous researchers have published papers on the combination of AMS with grazing. However, pasture-based AMS usually causes a reduction in milking frequency (MF) compared to indoors systems. The objectives of this meta-analysis were to review publications on the impacts of pasture-based AMS on MF and mitigation strategies. First, data from 43 selected studies were gathered in a dataset including 14 parameters, and on which a Principal Component Analysis (PCA) was performed, leading to the description of four clusters summarizing different management practices. Multiple pairwise comparisons were performed to determine the relationship between the highlighted parameters of MF on milk yield (MY). From these different analyses, the relationship between MF and MY was confirmed, the systems, i.e., Clusters 1 and 2, that experienced the lowest MF also demonstrated the lowest MY/cow per day. In these clusters, grazed grass was an essential component of the cow's diet and low feeding costs compensated MY reduction. The management options described in Clusters 3 and 4 allowed maintenance of MF and MY by complementing the cows' diets with concentrates or partial mixed ration supplied at the AMS feeding bin or provided at barn. The chosen management options were closely linked to the geographical origin of the papers indicating that other factors (e.g., climatic conditions or available grasslands) could be decisional key points for AMS management strategies.

Maximising Lucerne (Medicago sativa) Pasture Intake of Dairy Cows: 2-the Effect of Post-Grazing Pasture Height and Mixed Ration Level

Simple Summary

Pasture allocation has significant effects on grazing intensity, pasture utilisation and dry matter intake in grazing dairy herds. In sub-tropical Australian partial mixed ration (PMR), systems offering lucerne at an ideal pre-grazing pasture height and allocation, that ensures a proportion remains ungrazed, allows cows to selectively graze the top leafy stratum of the sward. When cows are only grazing the top leafy stratum, diet quality and intake is maximised in PMR systems irrespective of the amount of mixed ration offered.

Abstract

The effects of lucerne (Medicago sativa) post-grazing residual pasture height on pasture utilisation (vertical and horizontal), pasture intake and animal production were investigated in a sub-tropical partial mixed ration dairy system. The study took place at the Gatton Research Dairy, Southeast Queensland (−27.552, 152.333), with a 26-day adaptation period followed by two 8-day measurement periods during August and September 2018. A quantity of 30 multiparous Holstein-Friesian dairy cows were offered two levels of mixed ration, 7 and 14 kg dry matter (DM)/cow/day for low and high levels respectively, and five levels of pasture allocation, to achieve decreasing residual pasture heights. Pasture allocations measured from 5 cm above ground level for the low mixed ration groups averaged 12.7, 15.9, 19.8, 35.3 and 49.2 kg DM/cow/day, and for the high mixed ration groups averaged 5.0, 8.3, 10.3, 18.6, and 25.2 kg DM/cow/day, respectively. As pasture allocation decreased, cows were forced to graze further down into the pasture sward, and therefore residual pasture height declined. Total intake (kg DM/cow/day) declined as residual pasture height (expressed as % of the initial height) declined, irrespective of mixed ration level, decreasing by 0.5 kg DM/cow/day for every 10% decrease in residual pasture height. Low total intakes were associated with high non-esterified fatty acid (NEFA) levels in plasma, indicating mobilisation of fat tissue to maintain milk production. In the high allocation treatments, an area of pasture remained ungrazed and cows were only grazing the top leafy stratum where pasture intake rate and intake were highest. Therefore, to maximise intake in sub-tropical partial mixed ration (PMR) systems, lucerne pasture should be allocated so that cows are always grazing the top leafy stratum. This can be achieved by ensuring the pasture around faecal patches remains ungrazed.

Maximizing Lucerne (Medicago sativa) Pasture Intake of Dairy Cows: 1-the Effect of Pre-Grazing Pasture Height and Mixed Ration Level

The effect of lucerne (Medicago sativa L.) pre-grazing pasture height on pasture intake and milk production was investigated in a sub-tropical partial mixed ration (PMR) dairy system in south-east Queensland, Australia. The experiment involved a 26-day adaptation period followed by an eight-day measurement period during April and May 2018. Twenty-four multiparous Holstein-Friesian dairy cows were offered a mixed ration at either 7 (low) or 14 (high) kg dry matter (DM)/cow/day and allocated pastures at pre-grazing heights ranging from 23 to 39 cm. The targeted pasture intake was 14 and 7 kg DM/cow/day for cows offered the low and high mixed ration allowances respectively, with a total intake target of 21 kg DM/cow/day. Pasture structure did not limit pasture intake as the all groups left at least 12% of the allocated area ungrazed, and therefore could selectively graze pasture. There was no significant difference in intake between mixed ration levels, however intake had a positive linear relationship with pre-grazing pasture height. For every one cm increase in pasture height, intake increased by 0.3 kg DM/cow/day. Using a grazing strategy that ensures the some pasture remains ungrazed and the pre-grazing height of lucerne is approximately 39 cm above ground level will maximise pasture intake in sub-tropical PMR dairy systems.

The changing nature of dairy production in Victoria, Australia: are we ready to handle the planning and development of large, intensive dairy operations?

Around the world, dairy production continues to intensify, with farmers increasing stocking rates, feeding more supplements, and transitioning into fully housed systems. Dairy production in Victoria is no exception and farmers are starting a move towards intensive (i.e. permanently housed) dairy operations. Challenges associated with these transformations have included difficulties, or failure, to obtain planning approval and public concern around the effect of intensive developments on environmental degradation, animal welfare and industry image. We examined current land-use planning provisions, environmental requirements, animal-welfare regulations, industry guidelines and codes of practice for their applicability and suitability to the implementation of intensive dairy-production operations, particularly large-scale ones, in Victoria, Australia. Our aim was to clearly identify factors that have the potential to hinder the growth and expansion of existing dairy-production systems into intensive operations, and the establishment of new intensive dairy enterprises. The majority of legislation examined posed no obstacles to the development of large-scale intensive dairy operations. New definitions for intensive livestock production and the inclusion of an intensive dairy-farm category in the State planning provisions will reduce current confusion across and within planning departments. A standard methodology to determine separation distances is required and a code for intensive dairy farming would greatly assist with the planning-approval process. Many advisory publications fall short when applied to intensive dairy operations as they are currently written for pasture-based farms with limited infrastructure for regularly feeding or housing large herds of &gt;700 cows.

A whole-farm investment analysis of a partial mixed ration feeding system for dairy cows

Aim A dairy farm in south-west Victoria was analysed to discern the impact on profit and risk of changing from a feeding system in the base case where grain was fed in the dairy and forage in the paddock, to a partial mixed ration (PMR) or a formulated grain mix (FGM) feeding system. Context A PMR feeding system involves feeding a well formulated mixed ration to a grazing dairy herd and typically requires the use of specialised machinery to mix and feed out the forage and grain components of the ration together onto a feed pad. In a FGM feeding system, the same formulated ration fed in the PMR system is used, but the grain component of the ration is fed using the existing feeding system in the dairy with the hay component fed in the paddock. Method The analysis used data from experiments recently performed to establish milk responses to mixed ration feeding under Australian conditions. The case study farm comprised 244 ha and a herd of 420 self-replacing Holstein-Friesian cows that calved from May to July. The herd feeding system was based on grazed pasture, grain fed in the dairy at milking and hay fed in the paddock. Supplementary feed comprised ~50% of metabolisable energy in the diet of the milking cows. The pre-existing feeding system was altered to incorporate either a PMR system or a FGM system. An increased herd size of an extra 100 cows, plus the PMR or FGM systems, was also tested. Key results All systems analysed were more profitable than the base case. Increasing the herd by 100 cows was the most profitable option for both the PMR and FGM systems, but intensifying the system by increasing cow numbers also had the most variability in profit. Conclusions and implications The FGM system was the most profitable system because milk production could be increased without the costs of extra labour, depreciation and repairs and maintenance associated with using a mixer wagon to feed the ration. The FGM system presents an option for farmers to expand or intensify their systems without needing to construct a feed pad or invest in extra machinery and equipment.

Water-quality issues facing dairy farming: potential natural and built attenuation of nitrate losses in sensitive agricultural catchments

Context Dairy farming will be increasingly scrutinised for its environmental impacts, in particular for its impacts on freshwater quality in New Zealand and elsewhere. Management and mitigation of high nitrate losses is one of the greatest water-quality challenges facing dairy farming in New Zealand and other countries. Management of critical flow pathways and nitrate-attenuation capacity could offer potential solutions to this problem and help maintain dairy-farming productivity, while reducing its water-quality impacts. Aims The present paper reviewed the key water-quality issues faced by dairy farming and assessed potential of emerging edge-of-paddock technologies, and catchment-scale nutrient-attenuation practices, to reduce nitrate losses from dairy farming to receiving water bodies. Methods We developed a conceptual catchment-scale modelling analysis assessing potential natural and built attenuation of nitrate losses from dairy farming in the Tararua and Rangitikei catchments (located in the lower part of the North Island, New Zealand). Key results This exploratory analysis suggests that a reduction of greater than 25% in the river nitrate loads from dairy-farming areas could potentially be achieved by spatially aligning dairy land with areas of high subsurface nitrate-attenuation capacity, and by managing critical flow pathways using innovative edge-of-field technologies such as controlled drainage, drainage-water harvesting for supplemental irrigation, woodchip bioreactors, and constructed wetlands in the study catchments. Conclusions The research findings highlighted the potential to better understand, map and effectively utilise existing natural and new built-in nitrate-attenuation capacity to significantly reduce water-quality impacts from dairy farming across environmentally sensitive agricultural catchments. This knowledge and tools could help farmers close the gap between what can be achieved with current, in-field mitigation practises and the nitrogen-loss allocation imposed by regulatory authorities. Implications However, the research findings presented here are based on a coarse-scale, conceptual modelling analysis, and therefore further research is recommended to develop tools and practices to better understand, map and effectively utilise existing natural and new built-in nitrogen attenuation capacity at farm-scale to achieve productive and environmentally friendly pastoral dairy farming across agricultural landscapes.

Animal science Down Under: a history of research, development and extension in support of Australia’s livestock industries

This account of the development and achievements of the animal sciences in Australia is prefaced by a brief history of the livestock industries from 1788 to the present. During the 19th century, progress in industry development was due more to the experience and ingenuity of producers than to the application of scientific principles; the end of the century also saw the establishment of departments of agriculture and agricultural colleges in all Australian colonies (later states). Between the two world wars, the Council for Scientific and Industrial Research was established, including well supported Divisions of Animal Nutrition and Animal Health, and there was significant growth in research and extension capability in the state departments. However, the research capacity of the recently established university Faculties of Agriculture and Veterinary Science was limited by lack of funding and opportunity to offer postgraduate research training. The three decades after 1945 were marked by strong political support for agricultural research, development and extension, visionary scientific leadership, and major growth in research institutions and achievements, partly driven by increased university funding and enrolment of postgraduate students. State-supported extension services for livestock producers peaked during the 1970s. The final decades of the 20th century featured uncertain commodity markets and changing public attitudes to livestock production. There were also important Federal Government initiatives to stabilise industry and government funding of agricultural research, development and extension via the Research and Development Corporations, and to promote efficient use of these resources through creation of the Cooperative Research Centres program. These initiatives led to some outstanding research outcomes for most of the livestock sectors, which continued during the early decades of the 21st century, including the advent of genomic selection for genetic improvement of production and health traits, and greatly increased attention to public interest issues, particularly animal welfare and environmental protection. The new century has also seen development and application of the ‘One Health’ concept to protect livestock, humans and the environment from exotic infectious diseases, and an accelerating trend towards privatisation of extension services. Finally, industry challenges and opportunities are briefly discussed, emphasising those amenable to research, development and extension solutions.

Defining the key attributes of resilience in mixed ration dairy systems

Dairy feeding systems in Australia and New Zealand have seen an increase in the use of mixed rations to manage variability in climate and market conditions and enable a certain degree of resilience in the operating environment. In this review, resilience was defined as the ability of the farm system to respond to challenges, optimise productivity and profitability for a given set of circumstances, and persist over time. Specific attributes of a dairy system that contribute to resilience were considered as flexibility, consistency, adaptation, sustainability and profitability. A flexible forage base that uses water efficient forage species provides a consistent supply of nutrients from home-grown forages across the year and is a key driver of resilience. Consistent milk production from purchased concentrates adds value to the forage base and will ensure that the system is profitable in the long term. Appropriate investment in infrastructure and careful management of debt has a positive impact on technical and financial efficiency and improves overall economic performance and resilience of the system. Nutrients, feed wastage, cow comfort and welfare were also identified as key areas to focus on for improved sustainability. Future research investigating the interaction between forages and concentrates, and the subsequent milk production response will be important for the future resilience of mixed ration systems. Adaptive management at a tactical and strategic level across several technical areas will further underpin the resilience of a mixed ration dairy system, and minimise the impact of climate and price variability. This will have flow on benefits to animal welfare and resource sustainability, which will have a positive impact of the public perception of these systems within the Australian and New Zealand dairy industries.

Associations between immune competence, stress responsiveness, and production in Holstein-Friesian and Holstein-Friesian × Jersey heifers reared in a pasture-based production system in Australia

The objectives of this study were to assess antibody and cellular immune responses in first-lactation dairy heifers reared under a pasture-based production system and to investigate associations between immune competence and stress responsiveness, health, and productivity. A commercial vaccine was used to induce antibody and cellular immune responses and, based on measured responses, animals were classified as above average, average, and below average for each trait independently and in combination (overall immune competence). Overall immune competence phenotypic rankings were generated by combining standardized residual values for antibody and cellular responses measured in individual heifers. Cortisol responses to handling and yarding were used to assess stress responsiveness, worm egg counts were used to assess internal parasite burden, somatic cell counts to assess udder health and estimates of total daily milk volume, and milk fat and milk protein contents to assess productivity. A total of 393 Holstein-Friesian and Holstein-Friesian × Jersey crossbred heifers from 2 herds practicing seasonal calving in a pasture-fed production system were enrolled in the study. The immune competence phenotypes of individual heifers were assessed before their first mating and their subsequent performance during their first lactation was monitored. Animals with below-average antibody and cellular immune competence had higher serum cortisol concentrations compared with their counterparts following handling, suggesting they had a reduced ability to cope with management-induced stress. Furthermore, a significant negative (favorable) correlation was observed between antibody responses and stress responsiveness. Similarly, correlations between antibody responses and internal parasite burden were significant and negative (favorable). No correlations were observed between overall immune competence and milk yield, milk fat, and milk protein content.

The effect of a gradual or rapid dietary changeover from a grazed pasture to a conserved forage-based diet on milk yield, cow condition and rumen pH of late-lactation dairy cows

A 40-day experiment was conducted to determine the effect of a gradual versus rapid changeover from grazed pasture to grass silage on production and performance in late-lactation Holstein–Friesian cows. Eighty cows were assigned to one of the following two treatments (two groups of 20 cows each): (1) gradual changeover from grazed pasture to grass silage over a 10-day adaptation period (GRAD), or (2) immediate changeover from grazed pasture to grass silage, with no adaptation period (RAPID). In addition to grazed pasture and grass silage, cows also received equal daily amounts of supplementary concentrates throughout the 40 days (ranging from 6.6 to 7.5 kg DM/cow). The experiment was divided into three periods. In Period 1 (Days 1–12), all cows received a generous pasture allowance and no grass silage was offered. In Period 2 (Days 13–22), GRAD cows were gradually introduced to grass silage on a stepwise basis, while still consuming grazed pasture, while RAPID cows received grazed pasture until Day 17, before switching to ad libitum grass silage from Day 18 onward. In Period 3 (Days 23–40), all cows received ad libitum pasture silage and no grazed pasture. Feed intake, milk volume and composition, and rumen pH were measured. Treatment did not affect estimated dry-matter intake of grazed pasture or measured dry-matter intake of silage. Milk yield did not differ between treatments from Day 1 to Day 18 (mean 29.3 L/cow; P &gt; 0.05), but was greater in GRAD cows from Day 19 to Day 27 (mean 25.6 vs 22.1 L/cow; P &lt; 0.001). From Day 28 onward, no effect of treatment was detected apart from a 3-day juncture from Day 34 to Day 36, where milk yield in the GRAD treatment was greater (mean 22.8 vs 21.0 L/cow; P = 0.02). Milk fat and protein concentrations were unaffected by treatment throughout (mean 4.15% for milk fat, 3.37% for milk protein; P &gt; 0.05). Mean rumen pH was also unaffected by treatment in periods 1 and 2 (mean 6.27; P &gt; 0.05), but were greater in Period 3 in GRAD cows (6.34 vs 6.26 for GRAD vs RAPID; P &lt; 0.001), while the amount of time spent under pH 6.0 did not differ between treatments (mean 2.45 h/day; P &gt; 0.05). Changing the dietary forage source from grazed pasture to grass silage over a 10-day period increased milk yield, compared with having no dietary adaptation period, and the cumulative difference for the duration of this experiment amounted to 37 L/cow.

The Effects of System Changes in Grazed Dairy Farmlet Trials on Greenhouse Gas Emissions

Simple Summary

Dairy farm system practices aimed at reducing nitrate leaching can also reduce emissions of the greenhouse gases methane and nitrous oxide. A study comparing ‘current’ and ‘improved’ grazed dairy system practices showed that ‘improved’ systems generally produced lower greenhouse gas emissions while milk production was maintained. The amount of feed eaten per hectare was the key driver of total greenhouse gas emissions per area, with ‘improved’ systems generally exhibiting lower total enteric methane and less N flowing through the herd.

Abstract

An important challenge facing the New Zealand (NZ) dairy industry is development of production systems that can maintain or increase production and profitability, while reducing impacts on receiving environments including water and air. Using research ‘farmlets’ in Waikato, Canterbury, and Otago (32–200 animals per herd), we assessed if system changes aimed at reducing nitrate leaching can also reduce total greenhouse gas (GHG) emissions (methane and nitrous oxide) and emissions intensity (kg GHG per unit of product) by comparing current and potential ‘improved’ dairy systems. Annual average GHG emissions for each system were estimated for three or four years using calculations based on the New Zealand Agricultural Inventory Methodology, but included key farmlet-specific emission factors determined from regional experiments. Total annual GHG footprints ranged between 10,800 kg and 20,600 kg CO₂e/ha, with emissions strongly related to the amount of feed eaten. Methane (CH₄) represented 75% to 84% of the total GHG footprint across all modelled systems, with enteric CH₄ from lactating cows grazing pasture being the major source. Excreta deposition onto paddocks was the largest source of nitrous oxide (N₂O) emissions, representing 7–12% of the total GHG footprint for all systems. When total emissions were represented on an intensity basis, ‘improved’ systems are predicted to generally result in lower emissions intensity. The ‘improved’ systems had lower GHG footprints than the ‘current’ system, except for one of the ‘improved’ systems in Canterbury, which had a higher stocking rate. The lower feed supplies and associated lower stocking rates of the ‘improved’ systems were the key drivers of lower total GHG emissions in all three regions. ‘Improved’ systems designed to reduced N leaching generally also reduced GHG emissions.

Evaluating the economics of short-term partial mixed ration feeding decisions for dairy cows

Recent research in Australia has measured the marginal milk production responses of cows grazing perennial-based pastures to supplements offered as a partial mixed ration (PMR). In the present study, the milk responses to PMR feeding developed under a restricted pasture allowance were used to examine the contribution to farm profit of decisions about short-term feeding (weekly, monthly). A short-term, or tactical, decision was considered to be one where the infrastructure and equipment needed to mix and feed out a formulated ration were already available. The decision was, therefore, the choice of whether to feed supplements as grain in the dairy at milking and forage in the paddock, or to feed the supplements as a mixed ration on a feed pad. Both of these options were assumed to exist for the farmer decision-maker, with the comparison of rations being based solely on the costs of supplement and milk income. The Control diet in the experiments comprised cereal grain fed in the dairy and pasture silage fed in the paddock, simulating a situation where pasture available for grazing was limiting. The PMR diet consisted of cereal grain, maize grain, maize silage and lucerne hay combined in a mixer wagon and fed on a feed pad. The PMR + canola diet was similar to the PMR diet, but included canola meal. The profitability of the diets for different amounts of supplement intake was compared by estimating the total income from milk produced minus the cost of the supplements. The results indicated that feeding the diet comprising PMR plus canola meal in early lactation contributed more to farm profit than did the Control diet of feeding grain in the dairy and forage in the paddock, or PMR feeding without canola meal, because of higher milk production. At a supplement intake of 12 kg DM/cow.day, the PMR + canola diet added AU$0.97/cow.day and AU$2.11/cow.day more to profit than the Control and PMR without canola meal diets, respectively. For a farm already equipped with a feed pad and mixer wagon, the benefits of feeding a mixed ration exceed the costs in early lactation. In late lactation, each diet made similar contributions to farm profit because of similar milk production.

Chemical Composition and Nutritive Benefits of Chicory (Cichorium intybus) as an Ideal Complementary and/or Alternative Livestock Feed Supplement

Chicory is a perennial plant grown in different parts of the world, used as forage for livestock, as folklore remedies, or as a vegetable addition in human diets. There are several varieties of the chicory plant, known differently globally due to its numerous medicinal, culinary, and nutritional qualities. Most parts of the plant contain a potpourri of nutrients ranging within carbohydrates, proteins, vitamins, minerals, soluble fiber, trace elements, and bioactive phenolic compounds, which are responsible for the various nutritive, prophylactic, and therapeutic qualities of chicory. Inulin, coumarins, tannins, monomeric flavonoids, and sesquiterpene lactones are some of the major phytocompounds mostly found in chicory plants. The health-promoting activities attributed to chicory comprise, among others, anti-inflammatory, anticarcinogenic, antiviral, antibacterial, antimutagenic, antifungal, anthelmintic, immune-stimulating, and antihepatotoxic and its antioxidative qualities. As a versatile plant, chicory's chemical composition and use as a suitable livestock feed supplement or as an alternative feed ingredient (AFI) are thus reviewed.